{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a9da1810-9ad5-4197-a862-39db2a8597eb",
   "metadata": {},
   "source": [
    "# 实验五 分类模型的评估方法"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17a8055f-4981-4bd6-b3b1-c3a4f64634fe",
   "metadata": {},
   "source": [
    "## 步骤1 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6ce7d480-8863-43d5-823c-1988af3bb72e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_moons\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "label_size = 18 # Label size\n",
    "ticklabel_size = 14 # Tick label size\n",
    "\n",
    "# Generate moon-shaped data\n",
    "X, Y = make_moons(n_samples=1000, noise=0.25, random_state=42)\n",
    "\n",
    "# Split X and Y into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=42)\n",
    "\n",
    "# Plot the data\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "ax.scatter(X_train[y_train == 1, 0], X_train[y_train == 1, 1], color='red', label='Positive - Train')\n",
    "ax.scatter(X_test[y_test == 1, 0], X_test[y_test == 1, 1], color='orange', label='Positive - Test')\n",
    "ax.scatter(X_train[y_train == 0, 0], X_train[y_train == 0, 1], color='blue', label='Negative - Train')\n",
    "ax.scatter(X_test[y_test == 0, 0], X_test[y_test == 0, 1], color='green', label='Negative - Test')\n",
    "ax.set_xlabel('Feature 1', fontsize=label_size)\n",
    "ax.set_ylabel('Feature 2', fontsize=label_size)\n",
    "\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set legend fontsize\n",
    "plt.legend(prop={'size': 14})\n",
    "plt.savefig('one.png', dpi=300) # Make figure clearer\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb978c35-bc2c-474a-9102-2c626a24d781",
   "metadata": {},
   "source": [
    "## 步骤2 使用逻辑回归、SVM、决策树和随机森林模型进行分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c14d9dea-6833-4c1e-99ee-c941f43243c3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic regression model trained successfully...\n",
      "Support vector machine trained successfully...\n",
      "Decision tree trained successfully...\n",
      "Random forests trained successfully...\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "# Model Definition\n",
    "mdl_lr = LogisticRegression() # Logistic Regression\n",
    "mdl_svm = SVC() # Support Vector Machine\n",
    "mdl_dt = DecisionTreeClassifier() # Decision Tree\n",
    "mdl_rf = RandomForestClassifier(n_estimators=100) # Random Forests\n",
    "\n",
    "# Model Training\n",
    "mdl_lr.fit(X_train, y_train) # Logistic Regression\n",
    "print('Logistic regression model trained successfully...')\n",
    "\n",
    "mdl_svm.fit(X_train, y_train) # Support Vector machine\n",
    "print('Support vector machine trained successfully...')\n",
    "\n",
    "mdl_dt.fit(X_train, y_train) # Decision Tree\n",
    "print('Decision tree trained successfully...')\n",
    "\n",
    "mdl_rf.fit(X_train, y_train) # Random Forest\n",
    "print('Random forests trained successfully...')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17d31d95-5fc6-4538-b1ce-f2ddf17b6759",
   "metadata": {},
   "source": [
    "## 步骤3 根据不同的模型计算TP、FP、FN、TN值，绘制混淆矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "86e40968-45fa-4e76-9c65-9d8e9ec12efd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic Regression - TP: 126, FP: 18, FN: 22, TN: 134\n",
      "Support Vector Machine - TP: 137, FP: 7, FN: 5, TN: 151\n",
      "Decision Tree - TP: 130, FP: 14, FN: 13, TN: 143\n",
      "Random Forest - TP: 133, FP: 11, FN: 5, TN: 151\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Calculate TP, FP, FN, TN for each model\n",
    "def getTPFPFN(cm):\n",
    "    TP = cm[1, 1]\n",
    "    FP = cm[0, 1]\n",
    "    FN = cm[1, 0]\n",
    "    TN = cm[0, 0]\n",
    "    return TP, FP, FN, TN\n",
    "\n",
    "# TP, FP, FN, TN for each model\n",
    "tp_lr, fp_lr, fn_lr, tn_lr = getTPFPFN(cm_lr)\n",
    "tp_svm, fp_svm, fn_svm, tn_svm = getTPFPFN(cm_svm)\n",
    "tp_dt, fp_dt, fn_dt, tn_dt = getTPFPFN(cm_dt)\n",
    "tp_rf, fp_rf, fn_rf, tn_rf = getTPFPFN(cm_rf)\n",
    "\n",
    "# Print TP, FP, FN, TN for each model\n",
    "print(f\"Logistic Regression - TP: {tp_lr}, FP: {fp_lr}, FN: {fn_lr}, TN: {tn_lr}\")\n",
    "print(f\"Support Vector Machine - TP: {tp_svm}, FP: {fp_svm}, FN: {fn_svm}, TN: {tn_svm}\")\n",
    "print(f\"Decision Tree - TP: {tp_dt}, FP: {fp_dt}, FN: {fn_dt}, TN: {tn_dt}\")\n",
    "print(f\"Random Forest - TP: {tp_rf}, FP: {fp_rf}, FN: {fn_rf}, TN: {tn_rf}\")\n",
    "# Assuming X_train, y_train, X_test, y_test, mdl_lr, mdl_svm, mdl_dt, mdl_rf are already defined\n",
    "\n",
    "def confusion_matrix(y_pred, y_true):\n",
    "    '''\n",
    "    y_pred - predict classes\n",
    "    y_true - actual classes\n",
    "    '''\n",
    "    # Get the number of classes\n",
    "    n_classes = len(np.unique(y_true))\n",
    "    \n",
    "    # Initialize the confusion matrix with zeros\n",
    "    cm = np.zeros((n_classes, n_classes), dtype=int)\n",
    "    \n",
    "    # Fill the confusion matrix\n",
    "    for pred, actual in zip(y_pred, y_true):\n",
    "        cm[pred][actual] += 1\n",
    "    \n",
    "    return cm\n",
    "\n",
    "def cm_disp(cm, title='Confusion Matrix', save_fig=False):\n",
    "    ''' \n",
    "    Display confusion matrix\n",
    "    '''\n",
    "    global label_size, ticklabel_size\n",
    "    \n",
    "    # Create a figure and axis\n",
    "    fig, ax = plt.subplots(figsize=(6, 4))\n",
    "    \n",
    "    # Use seaborn to create a heatmap without color bar\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', ax=ax, annot_kws={'size': ticklabel_size}, cbar=False)\n",
    "    \n",
    "    # Set ticklabels\n",
    "    ax.set_xticklabels(['Positive', 'Negative'])\n",
    "    ax.set_yticklabels(['Positive', 'Negative'], rotation=90)\n",
    "    \n",
    "    # Set labels and title with custom font sizes\n",
    "    ax.set_xlabel('Predicted labels', fontsize=label_size)\n",
    "    ax.set_ylabel('True labels', fontsize=label_size)\n",
    "    ax.set_title(title, fontsize=label_size)\n",
    "    \n",
    "    # Set tick label font size\n",
    "    ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "    \n",
    "    if save_fig:\n",
    "        plt.savefig(f'{title.replace(\" \", \"_\")}_confusion_matrix.png', dpi=300, bbox_inches='tight')\n",
    "# Get confusion matrix of all models\n",
    "# Predictions for each model\n",
    "y_pred_lr = mdl_lr.predict(X_test)\n",
    "y_pred_svm = mdl_svm.predict(X_test)\n",
    "y_pred_dt = mdl_dt.predict(X_test)\n",
    "y_pred_rf = mdl_rf.predict(X_test)\n",
    "\n",
    "# Confusion matrices for each model\n",
    "cm_lr = confusion_matrix(y_pred_lr, y_test)\n",
    "cm_svm = confusion_matrix(y_pred_svm, y_test)\n",
    "cm_dt = confusion_matrix(y_pred_dt, y_test)\n",
    "cm_rf = confusion_matrix(y_pred_rf, y_test)\n",
    "\n",
    "# Display the confusion matrices\n",
    "save_flag = False\n",
    "cm_disp(cm_lr, title='Logistic Regression', save_fig=save_flag)\n",
    "plt.savefig('two.png', dpi=300) # Make figure clearer\n",
    "cm_disp(cm_svm, title='Support Vector Machine', save_fig=save_flag)\n",
    "plt.savefig('three.png', dpi=300) # Make figure clearer\n",
    "cm_disp(cm_dt, title='Decision Tree', save_fig=save_flag)\n",
    "plt.savefig('four.png', dpi=300) # Make figure clearer\n",
    "cm_disp(cm_rf, title='Random Forest', save_fig=save_flag)\n",
    "plt.savefig('five.png', dpi=300) # Make figure clearer\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3ac645e-66ee-4d2a-8f4c-5f006a57abc6",
   "metadata": {},
   "source": [
    "## 步骤4 任务2数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3d1ee83d-41c5-45f4-859e-285c516d15dd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_moons\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "label_size = 18 # Label size\n",
    "ticklabel_size = 14 # Tick label size\n",
    "\n",
    "# Generate moon-shaped data\n",
    "X, Y = make_moons(n_samples=1000, noise=0.4, random_state=42)\n",
    "\n",
    "# Split X and Y into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=42)\n",
    "\n",
    "# Plot the data\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "ax.scatter(X_train[y_train == 1, 0], X_train[y_train == 1, 1], color='red', label='Positive - Train')\n",
    "ax.scatter(X_test[y_test == 1, 0], X_test[y_test == 1, 1], color='orange', label='Positive - Test')\n",
    "ax.scatter(X_train[y_train == 0, 0], X_train[y_train == 0, 1], color='blue', label='Negative - Train')\n",
    "ax.scatter(X_test[y_test == 0, 0], X_test[y_test == 0, 1], color='green', label='Negative - Test')\n",
    "ax.set_xlabel('Feature 1', fontsize=label_size)\n",
    "ax.set_ylabel('Feature 2', fontsize=label_size)\n",
    "\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set legend fontsize\n",
    "plt.legend(prop={'size': 14})\n",
    "plt.savefig('six.png', dpi=300) # Make figure clearer\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a3d3e4-ab86-44d3-a5e6-151562bfdf17",
   "metadata": {},
   "source": [
    "### 使用逻辑回归和SVM进行分类，输出概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "581c3fa0-f212-4818-b721-f62e0091b652",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic regression model trained successfully...\n",
      "Support vector machine trained successfully...\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "# Model Definition\n",
    "mdl_lr = LogisticRegression() # Logistic Regression\n",
    "mdl_svm = SVC(probability=True) # Support Vector Machine, set probability to draw P-R Curve\n",
    "\n",
    "# Model Training\n",
    "mdl_lr.fit(X_train, y_train) # Logistic Regression\n",
    "print('Logistic regression model trained successfully...')\n",
    "\n",
    "mdl_svm.fit(X_train, y_train) # Support Vector machine\n",
    "print('Support vector machine trained successfully...')\n",
    "\n",
    "# Get confusion matrix of all models\n",
    "# Predict probabilities for each model\n",
    "y_proba_lr = mdl_lr.predict_proba(X_test)[:, 1] # Using probability of positive class\n",
    "y_proba_svm = mdl_svm.predict_proba(X_test)[:, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b86f14a-f7f1-429d-95ed-500725fc6700",
   "metadata": {},
   "source": [
    "### 调整阈值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "50914008-4536-40e1-9027-5b410dad87e6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def confusion_matrix(y_pred, y):\n",
    "    '''\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    '''\n",
    "    # Get the number of classes\n",
    "    n_classes = len(np.unique(y))\n",
    "    \n",
    "    # Initialize the confusion matrix with zeros\n",
    "    cm = np.zeros((n_classes, n_classes))\n",
    "    \n",
    "    # Fill the confusion matrix\n",
    "    for pred, actual in zip(y_pred, y):\n",
    "        cm[pred][actual] += 1\n",
    "    \n",
    "    return cm\n",
    "\n",
    "def get_prediction_from_proba(y_proba, threshold=0.5):\n",
    "    '''\n",
    "    y_proba - predict probabilities\n",
    "    threshold - threshold of probability\n",
    "    \n",
    "    y_pred - predict classes, y_proba > threshold is positive, otherwise negative\n",
    "    '''\n",
    "    y_pred = np.where(y_proba > threshold, 1, 0)\n",
    "    return y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1b3b33c-3498-4b44-88ef-fb77ca3aaeb7",
   "metadata": {},
   "source": [
    "## 步骤5 计算精确率、召回率、F1-Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9128f12b-6f54-4223-9024-39d70248dd90",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "When threshold = 0.0 - Precision: 0.4800, Recall: 1.0000, F1 Score: 0.6486\n",
      "When threshold = 0.1 - Precision: 0.5934, Recall: 0.9931, F1 Score: 0.7429\n",
      "When threshold = 0.2 - Precision: 0.6900, Recall: 0.9583, F1 Score: 0.8023\n",
      "When threshold = 0.3 - Precision: 0.7247, Recall: 0.8958, F1 Score: 0.8012\n",
      "When threshold = 0.4 - Precision: 0.7654, Recall: 0.8611, F1 Score: 0.8105\n",
      "When threshold = 0.5 - Precision: 0.8176, Recall: 0.8403, F1 Score: 0.8288\n",
      "When threshold = 0.6 - Precision: 0.8382, Recall: 0.7917, F1 Score: 0.8143\n",
      "When threshold = 0.7 - Precision: 0.9130, Recall: 0.7292, F1 Score: 0.8108\n",
      "When threshold = 0.8 - Precision: 0.9375, Recall: 0.6250, F1 Score: 0.7500\n",
      "When threshold = 0.9 - Precision: 1.0000, Recall: 0.3750, F1 Score: 0.5455\n",
      "When threshold = 1.0 - Precision: 0.0000, Recall: 0.0000, F1 Score: 0.0000\n",
      "[[156. 144.]\n",
      " [  0.   0.]]\n"
     ]
    }
   ],
   "source": [
    "def get_precision_recall_f1(y_pred, y):\n",
    "    '''\n",
    "    Compute precision, recall, and F1 score of binary classification\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    '''\n",
    "    epsilon = 1e-10\n",
    "    \n",
    "    # Compute confusion matrix\n",
    "    cm = confusion_matrix(y_pred, y)\n",
    "    \n",
    "    # Compute precision, recall, and F1 score\n",
    "    precision = cm[1, 1] / (cm[1, 1] + cm[1,0] + epsilon)\n",
    "    recall = cm[1, 1] / (cm[1, 1] + cm[0, 1] + epsilon)\n",
    "    f1 = 2 * (precision * recall) / (precision + recall + epsilon)\n",
    "    \n",
    "    return precision, recall, f1\n",
    "\n",
    "# Get predictions from probabilities\n",
    "for threshold in np.linspace(0, 1, 11):\n",
    "    y_pred_lr = get_prediction_from_proba(y_proba_lr, threshold)\n",
    "    precision_lr, recall_lr, f1_lr = get_precision_recall_f1(y_pred_lr, y_test)\n",
    "    print(f\"When threshold = {threshold:0.1f} - Precision: {precision_lr:.4f}, Recall: {recall_lr:.4f}, F1 Score: {f1_lr:.4f}\")\n",
    "\n",
    "print(confusion_matrix(y_pred_lr, y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ce39e7a-46e2-469b-a428-607fe36be608",
   "metadata": {},
   "source": [
    "## 步骤六 计算准确率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "462ce18d-ac6f-4f78-9c0f-979444626add",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic Regression Accuracy: 0.5200\n",
      "Support Vector Machine Accuracy: 0.9600\n",
      "Decision Tree Accuracy: 0.9100\n",
      "Random Forest Accuracy: 0.9467\n"
     ]
    }
   ],
   "source": [
    "def get_accuracy(cm):\n",
    "    '''\n",
    "    Compute accuracy from confusion matrix\n",
    "    cm - confusion matrix\n",
    "    '''\n",
    "    # Calculate total number of samples\n",
    "    total = np.sum(cm)\n",
    "    \n",
    "    # Calculate number of correct predictions (sum of diagonal elements)\n",
    "    correct = np.trace(cm)\n",
    "    \n",
    "    # Calculate accuracy\n",
    "    accuracy = correct / total\n",
    "    \n",
    "    return accuracy\n",
    "# Calculate accuracy for each model\n",
    "acc_lr = get_accuracy(cm_lr)\n",
    "acc_svm = get_accuracy(cm_svm)\n",
    "acc_dt = get_accuracy(cm_dt)\n",
    "acc_rf = get_accuracy(cm_rf)\n",
    "print(f\"Logistic Regression Accuracy: {acc_lr:.4f}\")\n",
    "print(f\"Support Vector Machine Accuracy: {acc_svm:.4f}\")\n",
    "print(f\"Decision Tree Accuracy: {acc_dt:.4f}\")\n",
    "print(f\"Random Forest Accuracy: {acc_rf:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5d74ddb-e3cd-4a7d-b8ea-cbe49dbe2d73",
   "metadata": {},
   "source": [
    "## 步骤7 绘制P—R曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4318b8fb-3174-4655-855c-9c6785181be1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import precision_recall_curve\n",
    "\n",
    "# Calculate precision and recall for various thresholds\n",
    "precision_lr, recall_lr, thresholds_lr = precision_recall_curve(y_test, y_proba_lr)\n",
    "precision_svm, recall_svm, thresholds_svm = precision_recall_curve(y_test, y_proba_svm)\n",
    "\n",
    "# Create the P-R curve of Logistic Regression and Support Vector Machine\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(recall_lr, precision_lr, marker='.', color='tab:blue', label='Model 2')\n",
    "ax.plot(recall_svm, precision_svm, marker='.', color='tab:orange', label='Model 3')\n",
    "ax.set_xlabel('Recall', fontsize=label_size)\n",
    "ax.set_ylabel('Precision', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "plt.legend(fontsize=ticklabel_size)\n",
    "\n",
    "# Add some threshold annotations of Logistic Regression\n",
    "for i in [0, int(len(thresholds_lr)/2), len(thresholds_lr)-1]:\n",
    "    plt.annotate(f'Threshold: {thresholds_lr[i]:.2f}', \n",
    "                    xy=(recall_lr[i]*0.8, thresholds_lr[i]), \n",
    "                    xytext=(5, 5), \n",
    "                    textcoords='offset points',\n",
    "                    fontsize=ticklabel_size)\n",
    "\n",
    "plt.savefig('P-R_Curve.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "345cdb04-8cd9-41ec-a1b0-77b6cc787cbe",
   "metadata": {},
   "source": [
    "## 步骤8 绘制F1-Recall曲线，确定最优判定阈值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c72b0e35-548f-4e4e-8db7-66aa53e28d19",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate F1 scores for SVM model\n",
    "f1_svm = 2 * (precision_svm * recall_svm) / (precision_svm + recall_svm)\n",
    "\n",
    "# Drawing a curve with Recall as x-axis and F1-score as y-axis\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(recall_svm, f1_svm, marker='.', color='tab:orange', label='Model 3')\n",
    "ax.set_xlabel('Recall', fontsize=label_size)\n",
    "ax.set_ylabel('F1 Score', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Add some threshold annotations of SVM where F1-score is maximum\n",
    "max_f1_index = np.argmax(f1_svm)\n",
    "plt.annotate(f'Threshold: {thresholds_svm[max_f1_index]:.2f}', \n",
    "                    xy=(recall_svm[max_f1_index]*0.8, f1_svm[max_f1_index]), \n",
    "                    xytext=(5, 5), \n",
    "                    textcoords='offset points',\n",
    "                    fontsize=ticklabel_size)\n",
    "\n",
    "# Adding a dashed line to indicate the maximum F1 score\n",
    "plt.axvline(x=recall_svm[max_f1_index], color='tab:orange', linestyle='--')\n",
    "plt.axhline(y=f1_svm[max_f1_index], color='tab:orange', linestyle='--')\n",
    "\n",
    "# Adding text annotations for maximum F1 score\n",
    "plt.text(recall_svm[max_f1_index]-0.8, f1_svm[max_f1_index]-0.05, f'Max F1 Score: {f1_svm[max_f1_index]:.4f}', \n",
    "         horizontalalignment='left', verticalalignment='bottom', fontsize=ticklabel_size, color='tab:orange')\n",
    "\n",
    "# Adding text annotations below x-axis of Recall where F1-score is maximum\n",
    "plt.text(recall_svm[max_f1_index]-0.3, -0.05, f'Recall: {recall_svm[max_f1_index]:.4f}', \n",
    "         horizontalalignment='left', verticalalignment='bottom', fontsize=ticklabel_size, color='tab:orange')\n",
    "\n",
    "plt.savefig('F1_Curve.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "316897ef-d759-4970-aa5b-1594c515aa80",
   "metadata": {},
   "source": [
    "### SVM进行分类，输出概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3a96e7fa-7d24-4b29-bf0e-2a2de4b503d3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support vector machine trained successfully...\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "# Model Definition\n",
    "mdl_svm = SVC(probability=True)\n",
    "\n",
    "mdl_svm.fit(X_train, y_train) # Support Vector machine\n",
    "print('Support vector machine trained successfully...')\n",
    "\n",
    "# Predict probabilities\n",
    "y_proba_svm = mdl_svm.predict_proba(X_test)[:, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0667ce71-7e0e-4f19-a388-f3461603c5eb",
   "metadata": {},
   "source": [
    "##  步骤9 生成混淆矩阵，计算敏感性和特异性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "56faf621-6089-4441-aa38-a1017a0feaa9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "When threshold = 0.00 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.01 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.02 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.03 - Sensitivity: 1.0000, Specificity: 0.0000\n",
      "When threshold = 0.04 - Sensitivity: 1.0000, Specificity: 0.0705\n",
      "When threshold = 0.05 - Sensitivity: 1.0000, Specificity: 0.1410\n",
      "When threshold = 0.06 - Sensitivity: 0.9931, Specificity: 0.2628\n",
      "When threshold = 0.07 - Sensitivity: 0.9931, Specificity: 0.3910\n",
      "When threshold = 0.08 - Sensitivity: 0.9861, Specificity: 0.4679\n",
      "When threshold = 0.09 - Sensitivity: 0.9792, Specificity: 0.5256\n",
      "When threshold = 0.10 - Sensitivity: 0.9792, Specificity: 0.5513\n",
      "When threshold = 0.11 - Sensitivity: 0.9792, Specificity: 0.6090\n",
      "When threshold = 0.12 - Sensitivity: 0.9792, Specificity: 0.6346\n",
      "When threshold = 0.13 - Sensitivity: 0.9792, Specificity: 0.6667\n",
      "When threshold = 0.14 - Sensitivity: 0.9653, Specificity: 0.6795\n",
      "When threshold = 0.15 - Sensitivity: 0.9583, Specificity: 0.6987\n",
      "When threshold = 0.16 - Sensitivity: 0.9583, Specificity: 0.7179\n",
      "When threshold = 0.17 - Sensitivity: 0.9583, Specificity: 0.7244\n",
      "When threshold = 0.18 - Sensitivity: 0.9583, Specificity: 0.7436\n",
      "When threshold = 0.19 - Sensitivity: 0.9583, Specificity: 0.7500\n",
      "When threshold = 0.20 - Sensitivity: 0.9514, Specificity: 0.7564\n",
      "When threshold = 0.21 - Sensitivity: 0.9444, Specificity: 0.7692\n",
      "When threshold = 0.22 - Sensitivity: 0.9375, Specificity: 0.7692\n",
      "When threshold = 0.23 - Sensitivity: 0.9306, Specificity: 0.7756\n",
      "When threshold = 0.24 - Sensitivity: 0.9306, Specificity: 0.7756\n",
      "When threshold = 0.25 - Sensitivity: 0.9236, Specificity: 0.7756\n",
      "When threshold = 0.26 - Sensitivity: 0.9236, Specificity: 0.7949\n",
      "When threshold = 0.27 - Sensitivity: 0.9097, Specificity: 0.7949\n",
      "When threshold = 0.28 - Sensitivity: 0.9097, Specificity: 0.7949\n",
      "When threshold = 0.29 - Sensitivity: 0.9028, Specificity: 0.8013\n",
      "When threshold = 0.30 - Sensitivity: 0.9028, Specificity: 0.8077\n",
      "When threshold = 0.31 - Sensitivity: 0.8958, Specificity: 0.8077\n",
      "When threshold = 0.32 - Sensitivity: 0.8958, Specificity: 0.8141\n",
      "When threshold = 0.33 - Sensitivity: 0.8889, Specificity: 0.8141\n",
      "When threshold = 0.34 - Sensitivity: 0.8819, Specificity: 0.8205\n",
      "When threshold = 0.35 - Sensitivity: 0.8819, Specificity: 0.8205\n",
      "When threshold = 0.36 - Sensitivity: 0.8750, Specificity: 0.8397\n",
      "When threshold = 0.37 - Sensitivity: 0.8750, Specificity: 0.8397\n",
      "When threshold = 0.38 - Sensitivity: 0.8681, Specificity: 0.8462\n",
      "When threshold = 0.39 - Sensitivity: 0.8611, Specificity: 0.8526\n",
      "When threshold = 0.40 - Sensitivity: 0.8542, Specificity: 0.8654\n",
      "When threshold = 0.41 - Sensitivity: 0.8472, Specificity: 0.8654\n",
      "When threshold = 0.42 - Sensitivity: 0.8472, Specificity: 0.8718\n",
      "When threshold = 0.43 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.44 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.45 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.46 - Sensitivity: 0.8472, Specificity: 0.8782\n",
      "When threshold = 0.47 - Sensitivity: 0.8403, Specificity: 0.8782\n",
      "When threshold = 0.48 - Sensitivity: 0.8403, Specificity: 0.8782\n",
      "When threshold = 0.49 - Sensitivity: 0.8333, Specificity: 0.8782\n",
      "When threshold = 0.51 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.52 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.53 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.54 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.55 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.56 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.57 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.58 - Sensitivity: 0.8194, Specificity: 0.8782\n",
      "When threshold = 0.59 - Sensitivity: 0.8056, Specificity: 0.8846\n",
      "When threshold = 0.60 - Sensitivity: 0.8056, Specificity: 0.8910\n",
      "When threshold = 0.61 - Sensitivity: 0.7986, Specificity: 0.8910\n",
      "When threshold = 0.62 - Sensitivity: 0.7986, Specificity: 0.8910\n",
      "When threshold = 0.63 - Sensitivity: 0.7986, Specificity: 0.8910\n",
      "When threshold = 0.64 - Sensitivity: 0.7917, Specificity: 0.8974\n",
      "When threshold = 0.65 - Sensitivity: 0.7917, Specificity: 0.8974\n",
      "When threshold = 0.66 - Sensitivity: 0.7917, Specificity: 0.9038\n",
      "When threshold = 0.67 - Sensitivity: 0.7847, Specificity: 0.9038\n",
      "When threshold = 0.68 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.69 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.70 - Sensitivity: 0.7569, Specificity: 0.9038\n",
      "When threshold = 0.71 - Sensitivity: 0.7569, Specificity: 0.9103\n",
      "When threshold = 0.72 - Sensitivity: 0.7500, Specificity: 0.9103\n",
      "When threshold = 0.73 - Sensitivity: 0.7500, Specificity: 0.9103\n",
      "When threshold = 0.74 - Sensitivity: 0.7431, Specificity: 0.9167\n",
      "When threshold = 0.75 - Sensitivity: 0.7361, Specificity: 0.9167\n",
      "When threshold = 0.76 - Sensitivity: 0.7153, Specificity: 0.9231\n",
      "When threshold = 0.77 - Sensitivity: 0.7083, Specificity: 0.9359\n",
      "When threshold = 0.78 - Sensitivity: 0.7014, Specificity: 0.9359\n",
      "When threshold = 0.79 - Sensitivity: 0.7014, Specificity: 0.9423\n",
      "When threshold = 0.80 - Sensitivity: 0.6944, Specificity: 0.9423\n",
      "When threshold = 0.81 - Sensitivity: 0.6875, Specificity: 0.9487\n",
      "When threshold = 0.82 - Sensitivity: 0.6806, Specificity: 0.9551\n",
      "When threshold = 0.83 - Sensitivity: 0.6736, Specificity: 0.9615\n",
      "When threshold = 0.84 - Sensitivity: 0.6528, Specificity: 0.9615\n",
      "When threshold = 0.85 - Sensitivity: 0.6319, Specificity: 0.9744\n",
      "When threshold = 0.86 - Sensitivity: 0.6181, Specificity: 0.9744\n",
      "When threshold = 0.87 - Sensitivity: 0.6042, Specificity: 0.9744\n",
      "When threshold = 0.88 - Sensitivity: 0.5694, Specificity: 0.9744\n",
      "When threshold = 0.89 - Sensitivity: 0.5556, Specificity: 0.9808\n",
      "When threshold = 0.90 - Sensitivity: 0.4931, Specificity: 0.9936\n",
      "When threshold = 0.91 - Sensitivity: 0.4375, Specificity: 1.0000\n",
      "When threshold = 0.92 - Sensitivity: 0.3611, Specificity: 1.0000\n",
      "When threshold = 0.93 - Sensitivity: 0.2986, Specificity: 1.0000\n",
      "When threshold = 0.94 - Sensitivity: 0.2361, Specificity: 1.0000\n",
      "When threshold = 0.95 - Sensitivity: 0.1736, Specificity: 1.0000\n",
      "When threshold = 0.96 - Sensitivity: 0.0972, Specificity: 1.0000\n",
      "When threshold = 0.97 - Sensitivity: 0.0278, Specificity: 1.0000\n",
      "When threshold = 0.98 - Sensitivity: 0.0000, Specificity: 1.0000\n",
      "When threshold = 0.99 - Sensitivity: 0.0000, Specificity: 1.0000\n",
      "When threshold = 1.00 - Sensitivity: 0.0000, Specificity: 1.0000\n"
     ]
    }
   ],
   "source": [
    "def confusion_matrix(y_pred, y):\n",
    "    '''\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    '''\n",
    "    # Get the number of classes\n",
    "    n_classes = len(np.unique(y))\n",
    "    \n",
    "    # Initialize the confusion matrix with zeros\n",
    "    cm = np.zeros((n_classes, n_classes))\n",
    "    \n",
    "    # Fill the confusion matrix\n",
    "    for pred, actual in zip(y_pred, y):\n",
    "        cm[pred][actual] += 1\n",
    "    \n",
    "    return cm\n",
    "\n",
    "def get_prediction_from_proba(y_proba, threshold=0.5):\n",
    "    '''\n",
    "    y_proba - predict probabilities\n",
    "    threshold - threshold of probability\n",
    "    \n",
    "    y_pred - predict classes, y_proba > threshold is positive, otherwise negative\n",
    "    '''\n",
    "    y_pred = np.where(y_proba > threshold, 1, 0)\n",
    "    return y_pred\n",
    "\n",
    "def get_sensitivity_specificity(y_proba, y, threshold=0.5):\n",
    "    '''\n",
    "    Compute sensitivity and specificity of binary classification\n",
    "    y_pred - predict classes\n",
    "    y - actual classes\n",
    "    threshold - threshold of probability\n",
    "    '''\n",
    "    epsilon = 1e-10\n",
    "    \n",
    "    # Get the confusion matrix\n",
    "    y_pred = get_prediction_from_proba(y_proba, threshold)\n",
    "    cm = confusion_matrix(y_pred, y)\n",
    "    \n",
    "    # Compute sensitivity and specificity\n",
    "    sensitivity = cm[1, 1] / (cm[1, 1] + cm[0, 1] + epsilon)\n",
    "    specificity = cm[0, 0] / (cm[0, 0] + cm[1, 0] + epsilon)\n",
    "    \n",
    "    return sensitivity, specificity\n",
    "\n",
    "# Get predictions from probabilities\n",
    "sen_spec_svm = []\n",
    "for threshold in np.linspace(0, 1, 100):\n",
    "    sensitivity, specificity = get_sensitivity_specificity(y_proba_svm, y_test, threshold)\n",
    "    print(f\"When threshold = {threshold:0.2f} - Sensitivity: {sensitivity:.4f}, Specificity: {specificity:.4f}\")\n",
    "    sen_spec_svm.append([sensitivity, specificity])\n",
    "\n",
    "# Convert to numpy array\n",
    "sen_spec_svm = np.array(sen_spec_svm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7356d352-0c49-4271-b396-6fd52a078731",
   "metadata": {},
   "source": [
    "## 步骤10 绘制特异性-敏感性曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "474bcfbe-0505-475d-a3f5-576d128a8b94",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ltQZ0aKYM60kdKyjSgws2VXu+3TSVYT3J9A1UifAMAADqtfIdCrNthQoxVO00DkNScmJ0rdWG4MO0DQAA0CC4NY3DqNWSEIQYeQYAAA1GTdM4TFNaseMnnSq1q3dyE13SKiFAlaKuIjwDAIAGpaZpHGcub/erni318i2X1m6BqNOYtgEAABqks6dxVGbpxoP6PiunFqtCXcc6z15gnWcAAIJftq1QGdaTWrf3qP6ycm+F44kx4Rp+aUv1b5+oy9s0VUyk6/+4/z4rR99lHGeaRx3l67xGePYC4RkAgPrj+6wc3fjXddWeEx5qqEfrBPW7KFH92ifq/a8zlLrpkPM40zzqHsJzHUJ4BgCgfnl88WYt3XjQ+Xl49yT9X7ckfbXHqjU/HlXW8Zo3UPnwN1cyAl2H+Dqv8cIgAADAaS/fcqnu7HOh1mfk6LLkBGcIHtYtSZK0/1hBWZDeY9UXO39Skb3iGOT6jBzCcz3GyLMXGHkGAKDh2rj/uEa+/nWF9tdH95AlJkJtEmPYqbAOYOQZAACgDuh5YRP9qmdLl2keknT/6bWjQwxp5shuGpXSOhDlwU8YefYCI88AAOD7rBytz8hRsd2hl5btcjkWahha8/QgRqADiJFnAACAOuSSVmVzo9fttVY4ZjdNbcg4riaxkUzjqCcIzwAAAD7QJjGm0h0LH/znZklM46gv2GEQAADAB2rasdBhShNTtyrbVvNyd6i7mPPsBeY8AwCAs5XvWHisoEgPnn558Exdzo/X/Ve107UXt1BEWIiybYVKtxYwrcNPmPMMAABQhyVZopRkiVK2rbDSaRzbD+XpwQWblBgboa4tLfpy91E5TKZ1BAumbQAAAPjB2dM4Qg1DT/+iox4afJHOi4uU9USxVu066gzXDlOalLqNaR11HNM2vMC0DQAAUJPyaRzJidHOaRkldode++JH/WnFngrnP3NdZ13XPUlJlih9sD5Ty7Yd1i+6ttDNlzEifS58ndcIz14gPAMAgHOVbStUn5krKz0WYkiNo8N1vKDE2da6SZS+fHJwbZVXb/g6rzFtAwAAoI5xmHIJzpKUebxQH6zPDFBFKEd4BgAACIB0a4HH13y6/Sc/VAJPEJ4BAAACoHxTFU9c26W5f4qB2wjPAAAAAXD2ahyGpPL9VarK1B2ax9VKbaga6zwDAAAEyKiU1hrQoZlzNQ5JyrCe1Nf7rHr18x8rnL8+I0eXtEqo7TJxBsIzAABAAJVvqnLm5+iIkErD82XJBOdAY9oGAABAHXNJqwT1bN3Ypa1n68aMOtcBhGcAAIA6JttWqM1ZuS5t32fZ2H2wDiA8AwAA1DHp1gLntt3l7KapDOvJwBQEJ8IzAABAHVPZMnahhuF8qRCBQ3gGAACoY8qXsStnGNKMkV1dXixEYBCeAQAA6qBRKa3VPD5CknRx81iNSmkd4IogEZ4BAADqpHYTP9ZPecWSpO2HT6jdxI8DXBEkwjMAAECd8+TizbJXeGGwrB2BRXgGAACoYz7fdaTS9pVVtKP2EJ4BAADqmCEdz6u0fXAV7ag9QRWe09LSNGzYMCUkJCgmJka9e/fWggULPLpHbm6unn32WXXv3l1xcXFKTExUSkqK5syZo1OnTvmpcgAAAPfNuuVShRoV20ddzkuDgWaYpmnWfFrgrVq1SkOHDlVERIRuvfVWWSwWpaamKj09XS+88IImTZpU4z1yc3PVq1cv7du3T/369dPll1+uoqIiffLJJ9q7d68GDx6szz77TCEh7v2dIi8vTxaLRTabTfHx8d5+RQAAABdPLt6slbuOKCYyVPuPn1K7ZjGaekMXXXRerJIsUcq2FSrdWqA2iTEsY1cFX+e1oAjPpaWl6tSpkw4cOKCvv/5aPXr0kCTl5+erT58+2rVrl3bs2KH27dtXe59Zs2bpqaee0qOPPqrZs2c724uLi9WvXz+lpaVp9erVGjBggFt1EZ4BAEBtOF5QrH4vrdTJYrskKcSQftmjpf616aAcZtnnmSO7sZxdJXyd14Ji2sbKlSu1d+9ejR492hmcJSkuLk6TJ09WaWmp5s2bV+N99u3bJ0kaNmyYS3tERISuueYaSdKRI0zEBwAAdUtRqV2Fp4OzJDlMaenGg84tvB2mNCl1m7JthQGqsOEIivC8atUqSdK1115b4Vh52+rVq2u8T5cuXSRJy5Ytc2kvKSnRihUrFBUVpT59+nhZLQAAgG+lWwtU01QBu2kqw3qyVuppyMICXYA79uzZI0mVTstISEhQYmKi85zqjBs3Tu+9955efvllrV+/XikpKSoqKtKyZcuUk5OjBQsWqGXLlj6vHwAAwBttEmMUYsg50lyV5MTo2imoAQuK8Gyz2SRJFoul0uPx8fE6cOBAjfeJiorSqlWrdO+99+r99993jlaHhITowQcfVL9+/aq9vqioSEVFRc7PeXl57n4FAACAc5ZkidLMkd00KXWb7NW8rrbjkI0XB/0sKKZt+IrVatU111yjb775Rh9//LFyc3N1+PBh/e1vf9O8efN0+eWXKycnp8rrZ86cKYvF4vxp1apVLVYPAAAaslEprbXm6UH65/gr9Mse51d6zqpdR2u5qoYnKMJz+Yhz+Qj02crfoqzJY489pnXr1mnp0qUaNmyYLBaLmjdvrvHjx2vWrFnat2+fXnnllSqvnzhxomw2m/MnKyvrnL4PAADAuUiyRKlPu6a6vntSpccLi+ya+9VefZ9VNhiYbSvUur1WXiT0oaCYtlE+13nPnj3q1auXy7GcnBxZrVZdeeWVNd7n448/VpMmTdS9e/cKxwYPHixJ2rBhQ5XXR0ZGKjIy0pPSAQAAfG5I5xbq2bqxNmbmurQv2XRQ2lT265aNo3Qot1CmWMrOl4Ji5HngwIGSpE8//bTCsfK28nOqU1xcrLy8PBUXF1c4dvRo2f/mIBwDAIBgkPpAX701ppfuuKK1Jv6iQ4XjB08HZ4ml7HwpKMLzkCFD1LZtWy1YsECbN292tufn52v69OkKCwvT2LFjne1Wq1U7d+6U1Wp1uU/fvn1VWlqq6dOnu7QXFRU52wYNGuS37wEAAOBLQzq30PQR3RQSWnOkYyk73wiK8BwWFqY333xTDodD/fv314QJE/TEE0/okksu0fbt2zV16lR16PDz37jmzJmjzp07a86cOS73efHFFxUXF6fnn39el19+uR577DE98MADuvjii7V8+XL16tVL48aNq+2vBwAA4JXeyU1qPMcQS9n5QlCEZ6lsRHjNmjXq16+fFi9erNdee01NmzbV+++/r9///vdu3ePSSy/Vhg0bdNddd+nw4cOaM2eO5s+fr5iYGE2bNk1ffvmlGjVq5OdvAgAA4FuXtErQr3rWsFeFUTu11HeGaVazWCCq5eu90gEAALzxfVaO1mfkKCIsRJM/3F7h+D/HX6E+7ZoGoLLA8XVeC5qRZwAAAFTvklYJuqd/W119cXOFnDXSHGoYTNvwAcIzAABAPVO+I2G5EEOaMbIruw/6AOEZAACgHhqV0lrxjcq29PjHuCtY49lHCM8AAAD1VMjpuRvN4tjHwlcIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAAD1VHGpXZL09V6rJCnbVqh1e63KthUGsqygFhboAgAAAOB7I19bq5PFDknS5A+3a+5X+3Qgp1AOs2zd55kju7F83Tlg5BkAAKCe+fyHw9qYmevSlnm8LDhLksOUJqVuYwT6HBCeAQAA6pmVO4/UeI7dNJVhPVkL1dQvhGcAAIB6ZnCn82o8J9QwlJwYXQvV1C+EZwAAgHpmSOcW6tm6sUtbTESoy+dLWlmUZImqxarqB14YBAAAqIdSH+irz384rFW7jqp1k2i98L+dLsc3Zubq+6wcXdIqIUAVBidGngEAAOqpIZ1baPqIbpJR+fFPtmWzdJ2HGHkGAACo53onN6m0/W+r0/W31eksXecBRp4BAADquUtaJehXPVtWeZyl69zHyDMAAEAD8PItl+rOPhdqfUaOIsJCNPnD7S7Hy5eu4yXC6jHyDAAA0EBc0ipB9/Rvq6svbl5hGrQhsXSdGwjPAAAAqPKlQrgiPAMAADQw6dYCmWe1mabYcdANhGcAAIAGpk1ijELOGmlmx0H3EJ4BAAAamCRLlGaO7OYSoB+9pj0vC7qB8AwAANAAjUpprbVPD1aPVo0lSTknSwJbUJAgPAMAADRQSZYo/XZIe0nSkg0HVFhsD3BFdR/hGQAAoAEb0KGZLkiIkq2wRP/ZcijQ5dR5hGcAAIAGLDTE0O2XXyhJev+b/QGupu4jPAMAADRwt1x2gSJCQ7TlgE3vfZ3BNt3VIDwDAAA0cE1jI9WlZbwkafKH29X3xZValJYZ4KrqJsIzAABAA5dtK9TmrFznZ4cpPb10q77ddyxwRdVRhGcAAIAGLt1aIPOsLQdNSaP+/o1u+/s3+u+WQyoudSjbVqh1e60NelpHWKALAAAAQGCV7zjoOCtAG5K+3ndMX+87ptjIUBUU2WVKCjGkmSO7aVRK60CUG1CMPAMAADRw5TsOhhplWw6GGoZe+lU3rXl6sH47+CI1jYnQidPBWSoL2ZNStzXIEWhGngEAAKBRKa01oEMzZVhPKjkx2rlV92PXdlRKmya6463vXM63m6Y2ZOSoSWyB2iTGNJitvQnPAAAAkFQ2Al1ZCL7ovNhKz39o4SaZZsOaxsG0DQAAANTIqKSt/CXDhjSNg/AMAACAaqVbC2TWcI7dNJVhPVkr9QQS4RkAAADVKl+NozqGpOTE6FqpJ5AIzwAAAKjW2atxVBogawjX9QUvDAIAAKBGZ67GcaygSA8u2ORy3DTVIFbfIDwDAADALeWrcWTbCivdVOWhf26q95uoMG0DAAAAHjl7Gke5hrCJCiPPAAAA8NiZ0ziycwv12Affuxyvr5uoEJ4BAABwTmqcxlEPN1Fh2gYAAAC8UuU0jnq4iQojzwAAAPDamdM4fsi26bn//uByvHwTlWCfvsHIMwAAAHwiyRKlPu2a6v+6JVXYVMWQFB4mrdtrDeoRaMM0zZp2W0QV8vLyZLFYZLPZFB8fH+hyAAAA6oxFaZmalLpV9kqSZm3OgfZ1XiM8e4HwDAAAULVsW6EyrCe15UCuZn6y0+VYqGFozdOD/D6Nw9d5jTnPAAAA8Ivy1ThMVRyrDdY50Mx5BgAAgF+1SYzRWVOgFWoYSk6MDkg93iA8AwAAwK+SLFEa1Ok85+dQw9CMkV2DbtRZIjwDAACgFnQ5v2y+8dAuzbXm6UFBu2EK4RkAAAC1pnwedLAiPAMAAABuIjwDAACg1mTbCoN6kxTCMwAAAPxu+6E8SdLy7T+p74srtSgtM8AVnRvCMwAAAPwq21aoL3YecX52mNKk1G1BOQJNeAYAAIBfpVsLKmyTUr5JSrAhPAMAAMCv2iTGKOSsXVJCDLFJCgAAAHC2JEuUZo7s5hKgW8Q3kiUqPHBFnSPCMwAAAPxuVEprrX16sF697VI1jgrXIdsp/e6DLTLNsyd01G2EZwAAANSKJEuUbrikpeaOuUzhoYY+3pqtVz//MdBleYTwDAAAgFqVktxEz4/oKkn604rd+mRrdoArcp/X4fm5557TwYMHfVELAAAAGohRKa11d982kqTHFn+v7YdsAa7IPV6H56lTp6pNmzYaMWKE/ve//wXdvBUAAAAExqRhnTSgQzMVlth197w0fbI1u86v/WyYXqbd5ORkZWaW7RBjGIYuuOACjRs3TnfffbdatmzpkyLrqry8PFksFtlsNsXHxwe6HAAAgKBjKyzRkJdXyXqiWFLZEnYzR3bTqJTWPrm/r/Oa1yPP6enp+uSTT/TLX/5SYWFhysrKchmN/uSTTxiNBgAAQKVOFpfqeEGx83Nd333Q6/BsGIaGDh2qpUuXKisrSzNmzFC7du1UWlqqjz76SNdff72Sk5M1ffp05kYDAADARbq1QI6zxlnr8u6DPl1t47zzztPTTz+t3bt3a8WKFbrlllsUHh7OaDQAAAAqVdnug6GGUWd3H/TbUnWDBw/WwoULdfDgQb388svq0KGDSktL9Z///Mc5Gj1jxgwdO3bMXyUAAACgjivffbA8PxuGNGNkVyVZogJaV1X8vs6zzWbTkSNHlJOTI8MwZJqmTNNUVlaWJk+erDZt2uiVV17xdxkAAACoo0altNaA9omSpLF9kn32sqA/+CU8l5aWavHixbr66qvVoUMHzZo1S0eOHFGLFi30zDPP6Pvvv9cf/vAHtW3bVidOnNDjjz+uv/3tb/4oBQAAAHXcorRMrd5jlSTNX5ehRWmZAa6oal4vVXem3bt3a+7cuXr33XdltVplmqYMw9DgwYN13333acSIEQoNDXWe73A49Oyzz2rGjBnq3Lmztm/f7qtSagVL1QEAAHgn21aovi+udHlpMNQwtObpQT6ZuuHrvBbm7Q2Ki4u1ZMkSzZ07V19++aUkyTRNNWnSRGPHjtV9992niy66qNJrQ0JCNH36dP3lL3/R3r17vS0FAAAAQaa61Tbq4rxnr8Nzy5Ytdfz4cefqGX369NF9992nW265RZGRkTVebxiGEhISlJWV5W0pAAAACDLlq22cPfJcb1fbOHbsmGJjY3Xffffp+++/19q1a3XHHXe4FZzLvfzyy3r77bdrPC8tLU3Dhg1TQkKCYmJi1Lt3by1YsMDjmvPz8zVlyhR17dpV0dHRaty4sXr27Klp06Z5fC8AAACcu2BbbcPrOc9vvPGGfv3rXysmJsZXNVVq1apVGjp0qCIiInTrrbfKYrEoNTVV6enpeuGFFzRp0iS37pOZmanBgwdr3759uvrqq9WjRw8VFRXpxx9/VGZmprZs2eJ2Tcx5BgAA8I0xb32r1XusuuvKZE25oYvP7uvrvObTFwb9pbS0VJ06ddKBAwf09ddfq0ePHpLKRpD79OmjXbt2aceOHWrfvn2197Hb7erTp4+2bdumjz/+WIMGDarQT1iY+zNZCM8AAADeW5SWqaeWbpUkGZJe/FU3ny1X5+u85vW0jZCQELVs2dLt89u0aeNRQJWklStXau/evRo9erQzOEtSXFycJk+erNLSUs2bN6/G+yxZskRpaWl64oknKgRnSR7XBQAAAO9k2wo1MXWr87MpaVLqNmXbCgNXVDV8khY9Hbz29PxVq1ZJkq699toKx8rbVq9eXeN9Fi1aJEm6+eablZWVpY8//li5ublq166d/u///k+xsbEe1QUAAADvNLjVNjxVXFyskBDPBrz37NkjSZVOy0hISFBiYqLznOqsX79ekrRmzRo9+uijKioqch5r1qyZFi9erKuuuqrK64uKilyuycvLc/crAAAAoBINbrUNT+Tm5urIkSNq3LixR9fZbDZJksViqfR4fHy885zqHDlyRJL00EMP6ZFHHlFWVpaOHj2qV199VTabTSNGjFB2dnaV18+cOVMWi8X506pVK4++BwAAAFwF22obHo88b9myRZs3b3ZpKyws1LvvvlvlNaZpKjc3V0uWLJHD4VDPnj09LtQXHA6HJOn666/Xiy++6Gx/6KGHdPDgQb300kt666239Mwzz1R6/cSJE/XYY485P+fl5RGgAQAAvDQqpbVW/nBEy3f8pIcGXeSzlwX9wePw/K9//UvPPfecS1teXp7uuuuuGq8t3677zADqjvIR56pGl8vfonTnPlarVTfccEOFY8OHD9dLL73knNpRmcjISI/WrwYAAIB7oiJCJUnxUeEBrqR6Hofnxo0bq3Xrn/82sH//foWEhOiCCy6o8pqQkBDFx8era9eumjBhgvr37+9Rn+Vznffs2aNevXq5HMvJyZHVatWVV15Z4306duwoq9Va6bSR8rbCwrr5ZicAAAACz+Pw/PDDD+vhhx92fg4JCVGzZs2Unp7u08LONHDgQM2cOVOffvqpbr31Vpdjn376qfOcmgwePFhr167Vjh07NHLkSJdjO3bskCQlJyf7pmgAAADUO16/MDhlyhQ9/vjjvqilSkOGDFHbtm21YMECl/nW+fn5mj59usLCwjR27Fhnu9Vq1c6dO2W1Wl3uc9dddykyMlJ/+ctfdPDgQZf7zJgxQ5J0yy23+PW7AAAAIHgFRXgOCwvTm2++KYfDof79+2vChAl64okndMkll2j79u2aOnWqOnTo4Dx/zpw56ty5s+bMmeNynzZt2ugPf/iDjhw5oksuuUTjx4/Xgw8+qO7du2vz5s2aMGGChgwZ4tfvAgAAgOAVNFvqDRo0SGvWrNGUKVO0ePFiFRcXq0uXLpo+fbpuv/12t+/z0EMPKTk5WX/4wx+0cOFClZaWqkuXLpo0aZLGjx/vx28AAACAYGeYHmz3V77KRmJioh544AGXNk89++yz53RdXeLrvdIBAAAaqkcWbtK/Nx/SM9d11rj+bX12X1/nNY/Cc0hIiAzDUMeOHZ0v2JW3ecput3t8TV1DeAYAAPCNYAnPHk3bGDBggAzDcFmqrrwNAAAAqO88Cs+rVq1yqw0AAADwRGFx2ayEvMKSAFdSPa9X2wAAAAC8sSgtU8t3/CRJ+svKH7UoLTPAFVXN6/B86tQpX9QBAACABijbVqiJqVudn01Jk1K3KdtWN3d99jo8t2jRQuPGjdPq1at9UQ8AAAAakHRrgRxnLV9hN01lWE8GpqAaeB2e8/LyNG/ePA0ePFjJycmaPHmydu/e7YvaAAAAUM+1SYxRyFlrTxiGlJwYHZiCauB1eJ47d64GDhwoScrMzNSMGTPUuXNnXXHFFXr99dd1/Phxr4sEAABA/ZRkidLMkd0UesbqbZGhIQoLqZuv5nm0znN1srKy9P777+v999/XDz/8UHZzw1B4eLiGDRumO+64Q9dff73Cw8N90V2dwDrPAAAAvpFtK9TeIyc0/eMd2nX4hEZcer5eubWH1/cN6CYp7tq4caPeffddLVy4UEeOHCnryDCUkJCgUaNG6Y477tAVV1zh625rHeEZAADAt77PytWI19bKNKVJ/9dJwy89X0mWqHO+X1CE53J2u12ffvqp3n33XX300UcqLCx7azIkJESlpaX+6rbWEJ4BAAB8b/Tfv9a6fWVTf0MMaebIbhqV0rqGqyrn67zm18kkoaGh+r//+z/985//1Pfff6/LLrtMkuTHvA4AAIAglm0r1DfpP78z5zDr1tJ1fg3PRUVFWrx4sYYPH64uXbpow4YN/uwOAAAAQa6uL13n0fbc7vryyy/13nvvacmSJcrLy3OONLdo0UKjR4/WnXfe6Y9uAQAAEOTKl647M0CH1KGl63wWnnfv3q13331X//jHP5SZWbalommaioqK0ogRI3TnnXfqmmuuUUgdXXYEAAAAgVe+dN3E1K3OAH3/wHZevTToS16H5zlz5ui9997T+vXrJZUFZsMwNHDgQN1xxx26+eabFRsb63WhAAAAaBhGpbTWgA7N9Nt/blJaRo4iw0MDXZKT1+H5t7/9rfPXHTt21B133KE77rhDrVq18vbWAAAAaKCSLFH6ZY8LlJaRoy93H9Vvh7QPdEmSfBCemzZtqltvvVV33nmnUlJSfFETAAAAoP7tEyVJm7JylXeqRPGNAr/ZntfhOTs7W2FhfnnvEAAAAA1YqybRapsYo33WAn2995iGdmkR6JK8X6qO4AwAAAB/KR99/nL30QBXUoalLwAAAFBnDejQTJL01R5rgCsp49Gw8eDBgyVJF154oebNm+fS5gnDMPT55597fB0AAAAalivaNlV4qKHM4yeVYS1QcmJMQOvxKDyvWrVKktSpU6cKbZ4wDMPjawAAANDwxESGqdeFCfpm33F9tedocIXnKVOmSJISExMrtAEAAAD+0L99M32z77hW77bqjj7JAa3FMMv3zobH8vLyZLFYZLPZFB8fH+hyAAAA6qVtB226/i9rFBMRqs1TrlV4qPuv7fk6r/HCIAAAAOq0i5Pi1TQmQgXFdm3cnxPQWrwOz88995xmz57t9vmvvvqqnnvuOW+7BQAAQAMREmKo3+kl6wK96obX0zZCQkLUokULHTp0yK3z27Rpo8zMTNntdm+6rROYtgEAAFA7lmw4oCc++F6XXGDRhw/2c/s6pm0AAACgwSnfLGXLQZuOFxQHrI5aD8/Hjx9Xo0aNartbAAAABLHm8Y3UqUWcTFNa+2Pgpm7Uanj+4IMPlJ+fr9atW9dmtwAAAKgH6sJW3R6t8yxJf/7zn/XnP//Zpe3o0aNq27ZtldeYpqnc3Fzl5eXJMAxdd911nlcKAACABm1Ah2aa+1W6vtpjlWmaAdl4z+PwnJubq4yMDJc2u91eoa0qQ4YM0bPPPutptwAAAGjgUpKbKDIsRIfzTmnPkRPq0Dyu1mvwODyPGDFCycnJkspGlO+++25ZLBa98sorVV4TEhKi+Ph4de3aVe3atTvXWgEAANCANQoP1eVtm+rL3Uf15e6jAQnPtb5UXX3CUnUAAAC1682v9un5j3/QgA7N9O7dvWs8v84tVedwOBpkcAYAAEDtG9ChmSTp233HdKqk9vcNYZ1nAAAABI3258WqRXwjFZU6tD6j9rfqJjwDAAAgaBiG4VyybmFaprJthbXav0fhOTQ0VKGhoerSpUuFNk9+wsI8fk8RAAAAkCSFhZZF2P9uyVbfF1dqUVpmrfXtUXg2TdP5U1mbJz8AAACAp7JthS5h2WFKk1K31doItEdDwF988YUkKTo6ukIbAAAA4G/p1gI5zhqHtZumMqwnlWSJ8nv/HoXngQMHutUGAAAA+EObxBiFGHIJ0KGGoeTE6Kov8iFeGAQAAEDQSLJEaebIbirfmNuQNGNk11oZdZZqKTzn5OQoLy+vNroCAABAPTcqpbWm3Vi2gEXXlhaNSmlda317HZ4PHTqkd999V8uWLatwbPv27brsssuUmJiohIQE9e/fX7t37/a2SwAAADRwl13YRJKUefxkrS5G4XV4fvvtt3XXXXdp1apVLu2FhYUaNmyYNm3a5FxhY+3atbr66qsZhQYAAIBX2iTGSJJshSU6XlBca/16HZ5XrFghSRo1apRL+zvvvKOsrCw1adJEc+fO1fvvv68LLrhABw8e1F//+ldvuwUAAEADFhURqpaNy+Y577MW1Fq/XofnjIwMSVKnTp1c2lNTU2UYhmbMmKF77rlHo0eP1ty5c2Wapj766CNvuwUAAEAD1+68WEnS3iMnaq1Pr8Oz1WpVfHy8oqJ+fsPR4XBo3bp1MgxDN910k7P9mmuuUUhIiHbt2uVttwAAAGjg2p6euhFUI892u11FRUUubVu3btXJkyfVpUsXJSQk/NxZSIgSEhJUUFB7XxAAAAD1U1COPCclJamoqEjp6enOtuXLl0uSrrzyygrnnzhxQk2aNPG2WwAAADRw7ZqVjTzvPRpE4blPnz6SpGnTpsnhcOjo0aN6/fXXZRiGhg4d6nJuenq6ioqKlJSU5G23AAAAaODaNSsbec7KKVRRqb1W+vQ6PD/88MOSpPfee0+NGzdWq1attH//frVp00bXX3+9y7mfffaZJKlnz57edgsAAIAG7ry4SMVGhsnuMJV57GSt9Ol1eO7du7fefvttxcbG6sSJEyouLlanTp2UmpqqsLAwl3PfffddSdKgQYO87RYAAAANnGEYalvLUzd8sj33mDFjdPjwYX377bfatWuXtm3bpu7du7ucU1xcrAkTJmjevHm67rrrfNEtAAAAGrjyqRt7j9bOghRhNZ/inqioKKWkpFR5PCIiQnfeeaevugMAAABq/aVBn4w8AwAAAIHQ9vTI875gG3kud+rUKeXk5KikpKTa81q3bu3rrgEAANDA/Dxt44RM05RhGH7tzyfh+eTJk5o1a5b++c9/6scff6zxfMMwVFpa6ouuAQAA0IBd2DRaIYaUf6pUR08U6by4Rn7tz+vwnJubqwEDBmj79u0yTdOta9w9DwAAAKhOo/BQXZAQrczjJ7XvaEHdD8/Tp0/Xtm3bFB4eroceekg33nijzj///ArL1AEAAAD+0K5ZjDKPn9Teoyd0Rdumfu3L64T773//W4Zh6JVXXtH999/vi5oAAAAAt7VrFqsvdh3V3iP+f2nQ69U2Dh48qJCQEN11112+qAcAAADwiHPFDav/l6vzOjw3adJEcXFxatTIv/NLAAAAgMqUr/W8/ZBN2bZCv/bldXju16+fbDabDh486It6AAAAAI9sPWiTJB3NL1bfF1dqUVqm3/ryOjw/9dRTCgsL0/Tp031RDwAAAOC2bFuhZvzvB+dnhylNSt3mtxFor8Nzr169NH/+fL3zzju65557tG/fPl/UBQAAANQo3Vogx1mrINtNUxnWk37pz+vVNtq2bStJCg0N1fz58zV//nznPOiqGIahvXv3ets1AAAAGrg2iTEKMeQSoEMNQ8mJ0X7pz+vwnJGRUaHt2LFjOnbsWJXX+HvbRAAAADQMSZYozRzZTU8t3SpJCjGkGSO7KskS5Zf+vA7P8+bN80UdAAAAwDkZldJaLy3bpeMFxZp/V28N6NDMb315HZ7HjBnjizoAAACAcxYaUjazoVlcpF/78fqFQQAAAKChIDwDAAAAbvJZeD5w4IAee+wxdenSRbGxsQoLc50RkpOToxkzZmjmzJlyOBy+6hYAAACoNV7PeZakFStW6Oabb1ZeXp5Ms2ydkLNX1EhISNCHH36o9evX64orrtCgQYN80TUAAABQa7weec7KytJNN90km82m4cOHa8mSJUpISKj03Lvvvlumaerf//63t90CAAAAtc7r8Dx79mzl5eXplltu0b///W+NHDlSERERlZ47dOhQSdKaNWvOqa+0tDQNGzZMCQkJiomJUe/evbVgwYJzrr2kpESXXnqpDMNQp06dzvk+AAAAaBi8nraxfPlyGYah6dOn13hucnKyIiMjlZ6e7nE/q1at0tChQxUREaFbb71VFotFqampuv3225WRkaFJkyZ5fM/p06frxx9/9Pg6AAAANExejzzv379fUVFRat++vVvnx8bG6sSJEx71UVpaqnHjxskwDH355ZeaO3eu/vjHP+r7779Xly5dNGXKFO3Zs8eje27cuFEzZ87UzJkzPboOAAAADZfX4TkkJMTt1TNKSkpks9kUFxfnUR8rV67U3r17NXr0aPXo0cPZHhcXp8mTJ6u0tNSjnQ6Li4s1duxYXXHFFXrwwQc9qgUAAAANl9fhuVWrVioqKlJWVlaN537xxRcqLS3VRRdd5FEfq1atkiRde+21FY6Vt61evdrt+02dOlV79uzRW2+9VWFVEAAAAKAqXofnIUOGSJLeeOONas8rLCzU008/LcMw9Itf/MKjPsqnZFQ2NSQhIUGJiYluT9tIS0vTrFmzNG3aNHXo0MGjOgAAANCweR2eH330UYWFhemPf/yj3nnnnUrPWbdunQYMGKDNmzcrOjpaDzzwgEd92Gw2SZLFYqn0eHx8vPOc6hQVFWns2LHq0aOHHn/8cY9qKL8+Ly/P5QcAAAANh9fhuW3btpozZ46Ki4t199136/zzz1dOTo4k6brrrlPr1q3Vv39/bdiwQYZh6O9//7uaN2/udeHnYvLkydqzZ4/efvtthYaGenz9zJkzZbFYnD+tWrXyQ5UAAACoq3yyPff48eOVmpqqpKQkHT58WMXFxTJNU5988okOHDgg0zSVlJSk1NRU3XbbbR7fv3zEuarR5by8vCpHpctt3LhRs2fP1u9//3t169bN4xokaeLEibLZbM4fd+Z5AwAAoP7wyfbckjRixAhdd911+uSTT7RmzRodOnRIdrtdLVq0UN++fTV8+HBFRkae073L5zrv2bNHvXr1cjmWk5Mjq9WqK6+8stp7bNmyRXa7XVOnTtXUqVMrHN+1a5cMw5DFYlFubm6l94iMjDzn7wAAAIDg57PwLEnh4eG64YYbdMMNN/jytho4cKBmzpypTz/9VLfeeqvLsU8//dR5TnU6dOige+65p9Jjb731liwWi2666SZFR0f7pmgAAADUO4ZpmqY/blxcXKxly5Zp165dioyMVM+ePdWvX79zuldpaak6duyogwcP6ptvvtGll14qScrPz1efPn20a9cubd++3bl6htVqldVqVWJiohITE2u8v2EY6tixo3bu3OlRXeXTRWw2m+Lj4z3+XgAAAPCNlBdW6Gh+kT55uL86J/2cy3yd1zweec7Pz9e//vUvSdKoUaMqncaQlpamm266SQcOHHBpv/zyy5WamqoWLVp4VmRYmN58800NHTpU/fv312233ab4+HilpqYqPT1dzz//vMuyc3PmzNG0adM0ZcqUSqdoAAAAAOfC4xcGP//8c40dO1avvPJKpcH5yJEjuu6665wvCp758+23357zlI5BgwZpzZo16tevnxYvXqzXXntNTZs21fvvv6/f//7353RPAAAAwBMejzx/9dVXkqTRo0dXevyll16S1WqVYRgaM2aMJkyYoNjYWM2fP19/+tOftGHDBi1ZskQ33XSTx8X27t1bn3zySY3nVfVSYFX8NHMFAAAA9YzH4fm7776rdpfAf/zjHzIMQ8OHD9e8efOc7S+//LKOHz+ud955R0uXLj2n8AwAAAAEksfTNrKzsxUWFqaLL764wrHt27fryJEjkqTf/va3FY4//PDDkqRNmzZ52i0AAAAQcB6H559++knx8fEKCal46XfffSdJioiIqHRlja5du8owDB06dOgcSgUAAAACy+PwbLfblZeXV+mxDRs2SJI6d+6siIiICsfDwsKUkJCgwsJCT7sFAAAAAs7j8HzeeeeptLRUe/furXDs66+/lmEYSklJqfL6EydOKCYmxtNuAQAAgIDzODz37NlTkvT3v//dpX3Pnj3avHmzpKp3+9u/f7+Ki4t1wQUXeNotAAAAEHAeh+fbbrtNpmnqT3/6k/7whz9o165d+vzzz3XzzTfLNE3FxMRo+PDhlV775ZdfSiqb+wwAAAAEG4/D880336wBAwaotLRUTz/9tC6++GJde+212rp1qwzD0GOPPaa4uLhKr120aJEMwzjnbboBAACAytgdZft2HM0v8ms/HodnSfrwww91/fXXu+weKEnjxo3Ts88+W+k1e/bs0bJlyyRJw4YNO8dyAQAAAFeL0jJ1vKBYkjRm3ndalJbpt7483iRFkiwWiz766CP9+OOPznnOKSkpuvDCC6u8Jjw8XB9++KHCw8PVtm3bcyoWAAAAOFO2rVATU7c6P5umNCl1mwZ0aKYkS5TP+zun8Fzuoosu0kUXXeTWucnJyUpOTvamOwAAAMBFurVAp2dsONlNUxnWk34Jz+c0bQMAAACoC9okxijEcG0LNQwlJ0b7pT/CMwAAAIJWkiVKM0d2c34OMaQZI7v6ZdRZIjwDAAAgyI1Kaa0mMWW7W8+/q7dGpbT2W1+EZwAAAAS90NNzN5rFRfq1H8IzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOAmwjMAAACCnt1hSpKO5hf5tR/CMwAAAILaorRMHS8oliSNmfedFqVl+q0vwjMAAACCVratUBNTtzo/m6Y0KXWbsm2FfumP8AwAAICglW4t0OkZG05201SG9aRf+iM8AwAAIGi1SYxRiOHaFmoYSk6M9kt/hGcAAAAErSRLlGaO7Ob8HGJIM0Z2VZIlyi/9EZ4BAAAQ1EaltFaTmAhJ0vy7emtUSmu/9UV4BgAAQNALPT13o1lcpF/7ITwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAAbiI8AwAAAG4iPAMAAABuIjwDAAAg6NkdpiTpaH6RX/shPAMAACCoLUrL1PGCYknSmHnfaVFapt/6IjwDAAAgaGXbCjUxdavzs2lKk1K3KdtW6Jf+CM8AAAAIWunWAp2eseFkN01lWE/6pT/CMwAAAIJWm8QYhRiubaGGoeTEaL/0R3gGAABA0EqyRGnmyG7OzyGGNGNkVyVZovzSH+EZAAAAQW1USms1iYmQJM2/q7dGpbT2W1+EZwAAAAS90NNzN5rFRfq1H8IzAAAA4CbCMwAAAOAmwjMAAADgJsIzAAAA4CbCMwAAAOCmoArPaWlpGjZsmBISEhQTE6PevXtrwYIFbl+/Zs0aPf744+rVq5eaNm2qRo0aqVOnTnrqqaeUm5vrv8IBAABQL4QFugB3rVq1SkOHDlVERIRuvfVWWSwWpaam6vbbb1dGRoYmTZpU4z1uuukmWa1W9evXT3feeacMw9CqVas0a9YsLV26VOvWrdN5551XC98GAAAAwSgownNpaanGjRsnwzD05ZdfqkePHpKkKVOmqE+fPpoyZYpuvvlmtW/fvtr7PProo7rzzjuVlJTkbDNNU7/5zW/0+uuva9q0afrrX//q1+8CAACA4BUU0zZWrlypvXv3avTo0c7gLElxcXGaPHmySktLNW/evBrv89RTT7kEZ0kyDEOTJ0+WJK1evdq3hQMAAKBeCYrwvGrVKknStddeW+FYeZs3wTc8PFySFBYWFAPxAAAACJCgSIt79uyRpEqnZSQkJCgxMdF5zrl4++23JVUezs9UVFSkoqIi5+e8vLxz7hMAAADBJyhGnm02myTJYrFUejw+Pt55jqc2b96sadOm6bzzztOTTz5Z7bkzZ86UxWJx/rRq1eqc+gQAAEBwCorw7C/p6em6/vrrZbfbtXDhQiUmJlZ7/sSJE2Wz2Zw/WVlZtVQpAAAA6oKgmLZRPuJc1ehyXl5elaPSVdm/f78GDRqko0ePaunSpRo0aFCN10RGRioyMtKjfgAAAFB/BMXIc/lc58rmNefk5Mhqtda4TN2ZMjIydNVVV+nQoUNavHixrr/+ep/VCgAAgPorKMLzwIEDJUmffvpphWPlbeXn1KQ8OB88eFCLFi3SjTfe6LtCAQAAUK8FRXgeMmSI2rZtqwULFmjz5s3O9vz8fE2fPl1hYWEaO3ass91qtWrnzp2yWq0u9zkzOC9cuFC//OUva+kbAAAAoD4IijnPYWFhevPNNzV06FD1799ft912m+Lj45Wamqr09HQ9//zz6tChg/P8OXPmaNq0aZoyZYqmTp3qbL/qqqu0f/9+XXHFFdqyZYu2bNlSoa8zzwcAAADOFBThWZIGDRqkNWvWaMqUKVq8eLGKi4vVpUsXTZ8+Xbfffrtb99i/f78k6ZtvvtE333xT6TmEZwAAAFTFME3TDHQRwap8lQ+bzab4+PhAlwMAANBgpbywQkfzi/TJw/3VOennXObrvBYUc54BAACA6tgdZePBR/OLajjTO4RnAAAABLVFaZk6XlAsSRoz7zstSsv0W1+EZwAAAAStbFuhJqZudX42TWlS6jZl2wr90h/hGQAAAEEr3Vogx1lv8NlNUxnWk37pj/AMAACAoNUmMUYhhmtbqGEoOTHaL/0RngEAABC0kixRmjmym/NziCHNGNlVSZYov/RHeAYAAEBQG5XSWk1iIiRJ8+/qrVEprf3WF+EZAAAAQS/09NyNZnGRfu2H8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAICgZ3eYkqSj+UV+7YfwDAAAgKC2KC1TxwuKJUlj5n2nRWmZfuuL8AwAAICglW0r1MTUrc7PpilNSt2mbFuhX/ojPAMAACBopVsLdHrGhpPdNJVhPemX/gjPAAAACFptEmMUYri2hRqGkhOj/dIf4RkAAABBK8kSpZkjuzk/hxjSjJFdlWSJ8kt/hGcAAAAEtVEprdUkJkKSNP+u3hqV0tpvfRGeAQAAEPRCT8/daBYX6dd+CM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAACAmwjPAAAAgJsIzwAAAICbCM8AAAAIenaHKUk6ml/k134IzwAAAAhqi9IydbygWJI0Zt53WpSW6be+CM8AAAAIWtm2Qk1M3er8bJrSpNRtyrYV+qU/wjMAAACCVrq1QKdnbDjZTVMZ1pN+6Y/wDAAAgKDVJjFGIYZrW6hhKDkx2i/9EZ4BAAAQtJIsUZo5spvzc4ghzRjZVUmWKL/0R3gGAABAUBuV0lpNYiIkSfPv6q1RKa391hfhGQAAAEEv9PTcjWZxkX7th/AMAAAAuCmownNaWpqGDRumhIQExcTEqHfv3lqwYIFH93A4HJozZ466d++uqKgoNWvWTLfccov27Nnjp6oBAABQXwRNeF61apX69eunr776SjfddJPuv/9+Wa1W3X777ZoxY4bb97nvvvv00EMPyW6366GHHtKwYcP00UcfKSUlRTt27PDjNwAAAECwM0zTNGs+LbBKS0vVqVMnHThwQF9//bV69OghScrPz1efPn20a9cu7dixQ+3bt6/2Pl988YUGDx6s/v3767PPPlNkZNmcmM8//1zXXHON+vfvr9WrV7tdV15eniwWi2w2m+Lj48/9CwIAAMArKS+s0NH8In3ycH91Tvo5l/k6rwXFyPPKlSu1d+9ejR492hmcJSkuLk6TJ09WaWmp5s2bV+N95s6dK0l6/vnnncFZkoYMGaKhQ4fqyy+/1O7du33/BQAAAFAvBEV4XrVqlSTp2muvrXCsvM2dEeNVq1YpJiZGffv2rXBs6NChbt8HAAAAdUtRiV2S9O2+Y37tJyjCc/nLfJVNy0hISFBiYmKNL/wVFBQoOztbbdq0UWhoaIXj5ffmxUEAAIDgMvK1tco7VSpJmvqfHRr52lq/9RXmtzv7kM1mkyRZLJZKj8fHx+vAgQNe3+PM8ypTVFSkoqKiCvfMy8urtm8AAAD4x6pdP2n9nkMubev3nNRHaXt0Vcfmzpzmq9f8giI81xUzZ87UtGnTKrS3atUqANUAAACgKje+4vo5Pz+/ykFUTwRFeC7/olWNCpe/RentPc48rzITJ07UY4895vycm5urCy+8UJmZmT55GKi78vLy1KpVK2VlZbGySj3Hs244eNYNA8+54ajqWZumqfz8fJ1//vk+6ScowvOZ85F79erlciwnJ0dWq1VXXnlltfeIiYlRUlKS0tPTZbfbK8x7rm5edbnIyEiXVTrKWSwW/kA2EPHx8TzrBoJn3XDwrBsGnnPDUdmz9uUgZ1C8MDhw4EBJ0qefflrhWHlb+Tk13aegoEBr11acRL58+XK37wMAAICGKSjC85AhQ9S2bVstWLBAmzdvdrbn5+dr+vTpCgsL09ixY53tVqtVO3fulNVqdbnPhAkTJEnPPPOMiouLne2ff/65li9frgEDBqhDhw5+/S4AAAAIXkERnsPCwvTmm2/K4XCof//+mjBhgp544gldcskl2r59u6ZOneoSeufMmaPOnTtrzpw5LvcZNGiQxo0bp6+++ko9evTQk08+qTFjxui6665TfHy8Xn/9dY/qioyM1JQpUyqdyoH6hWfdcPCsGw6edcPAc244autZB8X23OW+++47TZkyRV9//bWKi4vVpUsXPfLII7r99ttdzps6daqmTZumKVOmaOrUqS7HHA6H/vrXv+qNN97Qjz/+qNjYWA0aNEgvvPACo84AAACoVlCFZwAAACCQgmLaBgAAAFAXEJ4BAAAANxGeAQAAADcRns+SlpamYcOGKSEhQTExMerdu7cWLFjg0T0cDofmzJmj7t27KyoqSs2aNdMtt9zi3IgFdYO3z3rNmjV6/PHH1atXLzVt2lSNGjVSp06d9NRTTyk3N9d/hcNjvvhzfaaSkhJdeumlMgxDnTp18mGl8IavnnN+fr6mTJmirl27Kjo6Wo0bN1bPnj01bdo0P1SNc+GLZ52bm6tnn31W3bt3V1xcnBITE5WSkqI5c+bo1KlTfqocnnj//fd177336rLLLlNkZKQMw9D8+fM9vo/Pc5kJpy+++MKMiIgwY2NjzXHjxpmPP/642aZNG1OS+cILL7h9n/Hjx5uSzIsvvtj83e9+Z955551mZGSkabFYzO3bt/vxG8BdvnjWzZs3N0NDQ82BAweajzzyiPnoo4+aPXr0MCWZ7dq1M3/66Sc/fwu4w1d/rs80efJkMyYmxpRkduzY0ccV41z46jnv37/fbNeunWkYhnnNNdeYTz75pPnwww+b1113ndmtWzc/fgO4yxfPOicnx2zbtq0pyezXr5/5+OOPmw8++KDZrl07U5I5ePBg0263+/mboCYXXnihKclMTEx0/nrevHke38fXuYzwfFpJSYnZrl07MzIy0ty4caOzPS8vz+zSpYsZFhZm7t69u8b7rFy50pRk9u/f3zx16pSzfcWKFaZhGOaAAQP8Uj/c56tn/eKLL5qHDh1yaXM4HOb9999vSjIfeOABn9cOz/jqWZ9pw4YNZlhYmPnqq68SnusIXz3n0tJSMyUlxYyKijJXrlxZaT8ILF8965deesmUZD766KMu7UVFRWZKSoopyVy9erXP64dnPvvsMzMjI8M0TdOcOXPmOYVnf+QywvNpy5cvNyWZd911V4VjCxcuNCWZEydOrPE+t912W5V/6H7xi1+Yksxdu3b5pGacG18966ocOnTIlGR26dLFmzLhA75+1kVFRWa3bt3Mfv36mQ6Hg/BcR/jqOZefO3nyZH+UCR/w1bO+9957TUnmZ599VuHYpEmTTEnmBx984JOa4RvnGp79kcuY83zaqlWrJEnXXntthWPlbatXr3brPjExMerbt2+FY0OHDnX7PvAfXz3rqoSHh0sq2xkTgeXrZz116lTt2bNHb731lgzD8EmN8J6vnvOiRYskSTfffLOysrL0t7/9TS+++KI++OADnThxwncF45z56ll36dJFkrRs2TKX9pKSEq1YsUJRUVHq06ePl9WiLvBHLuO/7qeVTxpv3759hWMJCQlKTEyscWJ5QUGBsrOz1bVrV4WGhlY4Xn5vXhwMLF886+q8/fbbkir/lztqly+fdVpammbNmqUZM2awG2kd46vnvH79ekllLwM/+uijKioqch5r1qyZFi9erKuuuso3ReOc+OpZjxs3Tu+9955efvllrV+/XikpKSoqKtKyZcuUk5OjBQsWqGXLlj6vH7XLX7mMkefTbDabJMlisVR6PD4+3nmON/c48zwEhi+edVU2b96sadOm6bzzztOTTz55zjXCN3z1rIuKijR27Fj16NFDjz/+uE9rhPd89ZyPHDkiSXrooYf0yCOPKCsrS0ePHtWrr74qm82mESNGKDs723eFw2O+etZRUVFatWqVfv3rX2v16tX64x//qL/85S/au3evRo8erX79+vm0bgSGv3IZ4RnwkfT0dF1//fWy2+1auHChEhMTA10SfGTy5Mnas2eP3n777UpHL1A/OBwOSdL111+vF198URdccIESExP10EMP6dFHH5XNZtNbb70V4CrhC1arVddcc42++eYbffzxx8rNzdXhw4f1t7/9TfPmzdPll1+unJycQJeJOorwfFr530qq+ttHXl5elX9z8eQeZ56HwPDFsz7b/v37NWjQIB09elRLlizRoEGDvK4T3vPFs964caNmz56t3//+9+rWrZvPa4T3fPVnuvycG264ocKx4cOHS/p5agcCw1fP+rHHHtO6deu0dOlSDRs2TBaLRc2bN9f48eM1a9Ys7du3T6+88oovS0cA+CuXEZ5Pq27eS05OjqxWa6VzrM4UExOjpKQkpaeny263Vzhe3Vwt1B5fPOszZWRk6KqrrtKhQ4e0ePFiXX/99T6rFd7xxbPesmWL7Ha7pk6dKsMwXH4kadeuXTIMQ40bN/Z5/XCPr/5Md+zYUZIqfZblbYWFhedeKLzmq2f98ccfq0mTJurevXuFY4MHD5YkbdiwwctqEWj+ymWE59MGDhwoSfr0008rHCtvKz+npvsUFBRo7dq1FY4tX77c7fvAf3z1rKWfg/PBgwe1aNEi3Xjjjb4rFF7zxbPu0KGD7rnnnkp/pLIRi3vuuUd33nmnj6uHu3z1Z7o8NO3YsaPCsfK25OTkcy0TPuCrZ11cXKy8vDwVFxdXOHb06FFJUmRkpDeloo7wSy7zaGG7eqykpMRs27atGRkZaW7atMnZfubC62euA3j06FHzhx9+MI8ePepynzMX4y4qKnK2s0lK3eGrZ52enm5eeOGFZlhYmLl06dLaKh8e8NWzropY57lO8NVz3rdvnxkZGWmed9555oEDB1zuc+mll5qSzBUrVvj9+6BqvnrWQ4cONSWZzzzzjEv7qVOnnMf+8pe/+PW7wDM1rfNcm7mM8HyGlStXmuHh4WZsbKw5fvx4ly0/n3/+eZdzp0yZYkoyp0yZUuE+48aNY3vuOs4Xz7p8q9ArrrjCnDJlSqU/CDxf/bmuDOG57vDVcy7fObJp06bmuHHjzN/85jdmcnKyKcmcMGFCLX0bVMcXz3rTpk1mXFycKcns3bu3+eijj5r333+/c8vuXr16mYWFhbX4rVCZuXPnmmPGjDHHjBlj9uzZ05Rk9u3b19n2r3/9y3lubeYywvNZvv32W/MXv/iFabFYzKioKPOyyy4z33///QrnVfeQ7Ha7+eqrr5pdunQxIyMjzaZNm5o33XQTOwvWMd4+a0k1/qBu8MWf68oQnusWXz3njz76yOzfv78ZGxtrNmrUyOzVq5f597//3c/VwxO+eNa7d+8277rrLrN169ZmeHi4GRUVZXbr1s2cNm2aWVBQUAvfAjUZM2ZMtf+NPfO51mYuM0zTND2b6AEAAAA0TLwwCAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAAAAuInwDAAAALiJ8AwAAAC4ifAMAJAkjR07VoZhaOzYsZUet9vtmj17tnr06KGYmBgZhiHDMPTvf/9bknTVVVfJMAxNnTrVZzWV97Fq1Sqf3RMAvBEW6AIAoC4zTVNLlizRggULtHHjRh05ckShoaFq3ry5kpKS1Lt3b/Xv319DhgxRfHx8oMv1q0ceeURz5syRJEVERKh58+aSpEaNGtV6Lbm5uXrllVecdTVu3LjWawDQMBGeAaAKubm5GjFihFavXu1sCwsLU3R0tDIzM7Vv3z6tXbtWf/rTnzRv3rwqR2yDRVJSkjp27KikpKQKx/Lz8/XGG29IkmbNmqUnnnhChmG4nNO6dWt17NhRiYmJPqupY8eOkqTo6GiX9tzcXE2bNk1S2Yg54RlAbTFM0zQDXQQA1EU33HCD/vOf/yg0NFSPPPKI7r33XrVr104hISEqLS3Vjh07tGzZMi1YsECPPPJI0Ifn6qSlpal3796SyoJ0bGxsQOvJyMhQmzZtJEnp6elKTk4OaD0AGg7CMwBUYs+ePerQoYMkaebMmXr66aerPb+wsFBRUVG1UVpArF69WldddZWksqksgUZ4BhAovDAIAJXYvHmz89c33nhjjeefHZyTk5NlGIbmz5+v/Px8TZw4UR07dlRUVJQSExM1YsQIffvttzXed9OmTbr77rvVrl07RUdHKzY2VpdccomeeeYZWa3Waq8tKCjQ7NmzNXDgQCUmJioyMlIXXHCBBg4cqJdfflk//fSTy/mVvTA4f/58GYbhDM7Szy/xnd3uzguDP/zwg37zm9/o4osvVlxcnGJjY9WxY0fdeuutWrp0qRwOh8v5lb0weNVVVzmDsyS1adOm0ppuvfVWGYahYcOGVfv79OOPPyokJIQXEwG4hTnPAFCDAwcOqHPnzud0bU5OjlJSUrRr1y5FRESoUaNGOnbsmD788EP95z//0dy5c3X33XdXeu2UKVM0ffp050hvdHS0SkpKtGXLFm3ZskVvv/22Pv74Y/Xo0aPCtRs3btSIESOUlZUlSQoJCZHFYtGhQ4d08OBBffnll87pKNWJiopS8+bNVVxcrJycHElyvigoSU2aNHH79+Kll17SpEmTnAG5UaNGCg8P1+7du7V7924tWrRIOTk5Nc5fbtKkiRITE51/eUhMTFRoaGiFmu677z4tWrRIy5cvV2Zmplq3bl3p/d58802ZpqkOHTq4/GUAACrDyDMAVCIlJcX5Qtzjjz+u3bt3n9N9pk2bpiNHjmjx4sUqKCiQzWbTjh07NHDgQDkcDt17773auHFjheteeeUVPffcc4qNjdXMmTOVnZ2tgoICnTx5UuvXr9fgwYOVnZ2tG264QSdOnHC5NisrS0OHDlVWVpZatWqlhQsXKj8/X8ePH1dhYaG2bt2qqVOnqlmzZjXWP2rUKB0+fFipqanOtsOHDzt/zmyvzuuvv66nn35aDodDN9xwgzZt2qTCwkLl5eXp2LFj+vTTTzVq1CiFhNT8n6XU1FSlpaU5P6elpVVa01VXXaXOnTvL4XDorbfeqvReJSUlmj9/viRpwoQJbn0XAA2cCQCo1Pjx401JpiTTMAyzR48e5gMPPGC+9dZb5tatW02Hw1HltRdeeKHz2hUrVlQ4fvLkSbN9+/amJHPYsGEux44ePWpGR0ebhmFUeq1pmmZJSYnZq1cvU5L5pz/9yeXYr3/9a1OS2bRpUzMzM9Pt7ztmzBhTkjlmzJgKx7744gvn96nKwIEDTUnmlClTXNqPHz9uxsXFmZLMW2+9tdrft7OV9/nFF1+4tKenpzuPpaenV3n9K6+8YkoyL7jgArO0tLTC8SVLlpiSzIiICPPo0aNu1wWg4WLkGQCq8Nprr2ny5MmKiYmRaZratGmTXnvtNd1zzz3q1q2bWrRooccee6zC3OEz9e3bV0OGDKnQHhUVpd/97neSpGXLlslmszmP/eMf/9DJkyd12WWXVXqtVLZk3m233SZJWr58ubO9oKBAixYtkiQ9/fTTatWqledf3MeWLFmi/Px8hYeHa/bs2RWWuPOnMWPGKDo6WgcOHND//ve/Csfnzp0rSfrVr37l0yX2ANRfhGcAqEJYWJiee+45HTx4UO+9957GjRunSy65RBEREZKkI0eO6E9/+pO6du2q7777rtJ7DB48uMr7lx9zOBwuUzfWrFkjSdq2bZtatGhR5c9zzz0nSdq/f7/z2vXr16ukpESSNHz4cC++ve+sW7dOktSrV69K15D2p8aNG2vUqFGSfg7K5fbv36/PPvtMElM2ALiP8AwANbBYLPr1r3+tuXPnavPmzbLZbPrss8+c4dRqtepXv/qVTp06VeHali1bVnnfM48dOXLE+etDhw5JKlv+7qeffqryJy8vT5J08uRJ57WHDx92/vrCCy88x2/sW+U1Baqe++67T5L0v//9TwcPHnS2v/nmm3I4HOrYsSMvCgJwG+EZADzUqFEjXX311froo480ZswYSWUrcixbtqzCudVNUajqmN1ul1QW+kzTrPEnIyPD+y9VC2pzusaZevfurZ49e8putztfHLTb7Zo3b54kafz48QGpC0BwIjwDgBfO/N/9u3btqnD8wIEDVV575rHzzjvP+esWLVpIkrZu3epxPWdOizhzOkcgldcUyJBfPvr81ltvyeFwOEehIyMjnX8BAgB3EJ4BwAtnblMdGRlZ4fgXX3xR5bXlx0JCQlzWau7bt68k6ZtvvvE4AF922WXOOdn/+c9/PLrWX6688kpJZfOxs7OzfXLPM5e0M93Y8XD06NGKj49XZmamli9f7pz/PHLkSF4UBOARwjMAVCI9Pd2ttZ3feecd56979uxZ4fiaNWsq3bXu1KlTevnllyVJQ4cOddkY5I477lBUVJTsdrt+85vfOKdxVMbhcCg3N9f5OTo6Wrfeeqsk6cUXX3RukhJIN998s+Lj41VaWqpHH33UJ9t7x8fHO3995vevSkxMjO644w5J0vPPP+9ceYMXBQF4ivAMAJXYvn27OnfurOuuu07vvvuuy5SDkpISbdq0SXfddZdmz54tqWxebb9+/Srcx2Kx6Fe/+pWWLFmi0tJSSdLOnTt13XXXaefOnQoNDXWumlGuRYsWevHFFyVJH3/8sa655hqtXbvWGaJN09TOnTs1e/Zsde3aVf/9739drn/hhReUmJioY8eOqW/fvlq8eLEKCwslSUVFRdqyZYt+97vf6b333vPNb1YNLBaLZs2aJUlatGiRfvnLX7psf56Tk6OPP/5YN954o/MlyJo0btzY+cLlvHnznL+31SmfurFu3TrZ7XZeFARwbgKyujQA1HHLli1zbsJR/hMREWE2adLENAzDpb1nz57mwYMHXa4v3yRl9uzZZseOHU1JZmRkpGmxWFw2Xvn73/9eZQ2zZs0yQ0NDXfpv2rSpGR4e7tL/+++/X+HaDRs2mC1btnSeExoaaiYkJLjUfvbmKv7aJKXcjBkzzJCQEOd9oqKinJunlP/k5OS4XFPefvYmKaZpmtOnT3cej4yMNFu1amVeeOGF5qhRo6qssV+/fs5r/vjHP1Z5HgBUhZFnAKjE0KFDtWfPHv35z3/WzTffrM6dOysyMlK5ubmKjo5W+/btdcstt2jhwoVKS0vT+eefX+l9EhIS9N133+npp59W69atVVRUpCZNmmj48OFau3ZttSs9/O53v9POnTv16KOPqnv37mrUqJFyc3MVGxurlJQUPfnkk1q3bp1Gjx5d4dqePXvqhx9+0IsvvqgrrrhCcXFxKigo0AUXXKCrrrpKs2fPrvQ6f5o4caK+//57jR8/XhdddJGkslH0jh076rbbblNqaqrLdIyaTJo0SX/+85912WWXKTw8XAcOHND+/ftdlus728033yxJvCgI4JwZpumDyWcAABfJycnav3+/5s2bp7Fjxwa6HJw2fPhw/fe//9Vtt92mBQsWBLocAEGIkWcAQIOwb98+54uC999/f4CrARCsCM8AgHovLy9P999/vxwOhy6//HL1798/0CUBCFJhgS4AAAB/eeKJJ/TBBx/o8OHDKi4uVlhYmF555ZVAlwUgiDHyDACot6xWqzIzMxUREaE+ffpo2bJluuKKKwJdFoAgxguDAAAAgJsYeQYAAADcRHgGAAAA3ER4BgAAANxEeAYAAADcRHgGAAAA3ER4BgAAANxEeAYAAADcRHgGAAAA3ER4BgAAANz0/7mOLcUAxNXsAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use sen_spec_svm to draw specificity-sensitivity curve\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(sen_spec_svm[:, 1], sen_spec_svm[:, 0], marker='.', color='tab:blue', label='SVM Model')\n",
    "ax.set_xlabel('Specificity', fontsize=label_size)\n",
    "ax.set_ylabel('Sensitivity', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set axis limits\n",
    "ax.set_xlim([0, 1.01])\n",
    "ax.set_ylim([0, 1.01])\n",
    "\n",
    "# Save the figure\n",
    "plt.savefig('Specificity_Sensitivity_Curve.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac46ce36-c4e7-44fc-b1a7-e499ed33991a",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 步骤11 绘制曲线图PROC曲线并计算AUC值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d9ba13b0-f436-4586-a0c3-458cf9497717",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the ROC Curve (AUC): 0.9388\n"
     ]
    }
   ],
   "source": [
    "# Use sen_spec_svm to draw ROC curve\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "ax.plot(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0], marker='.', color='tab:red', label='SVM Model')\n",
    "ax.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Classifier')\n",
    "ax.set_xlabel('False Positive Rate (1 - Specificity)', fontsize=label_size)\n",
    "ax.set_ylabel('True Positive Rate (Sensitivity)', fontsize=label_size)\n",
    "ax.tick_params(axis='both', which='major', labelsize=ticklabel_size)\n",
    "\n",
    "# Set axis limits\n",
    "ax.set_xlim([-0.01, 1.00])\n",
    "ax.set_ylim([-0.01, 1.01])\n",
    "\n",
    "# Save the figure\n",
    "plt.savefig('ROC_Curve.png', dpi=300)\n",
    "\n",
    "# Add surface\n",
    "ax.fill_between(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0], color='tab:blue', alpha=0.2)\n",
    "\n",
    "plt.savefig('AUC.png', dpi=300)\n",
    "plt.show()\n",
    "\n",
    "# Calculate AUC\n",
    "from sklearn.metrics import auc\n",
    "roc_auc = auc(1 - sen_spec_svm[:, 1], sen_spec_svm[:, 0])\n",
    "print(f\"Area Under the ROC Curve (AUC): {roc_auc:.4f}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
